Occupant position detection

ABSTRACT

A computing device in a vehicle can be programmed to receive an occupant position measurement from at least one of an acoustic and a light sensor, determine an estimated occupant size based on occupant weight, estimate a vehicle seat position based on the occupant position measurement, and, control a vehicle occupant safety device based on the estimated occupant size and estimated vehicle seat position.

BACKGROUND

Vehicles can be equipped to operate in both autonomous and occupantpiloted mode. Vehicles can be equipped with computing devices, networks,sensors and controllers to acquire information regarding the vehicle'senvironment and to pilot the vehicle based on the information. Acomputing device can also be equipped with computing devices, networks,sensors and controllers to acquire information regarding the vehicle'soccupants and to pilot the vehicle based on the information. Vehicles inautonomous mode can provide occupants with the ability to move seatingaround to socialize, recline seats to sleep or view video screens, freefrom the need to watch the roadway.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example vehicle.

FIG. 2 is a diagram of an example infrared emitter and receiver.

FIG. 3 is a diagram of an example ultrasound transceiver.

FIG. 4 is a diagram of an example human model in a vehicle seat.

FIG. 5 flowchart diagram of an example process to apply retractor forcebased on an occupant model.

FIG. 6 is a flowchart diagram of an example process to set retractorforce based on an occupant model.

DETAILED DESCRIPTION

Vehicles can be equipped to operate in both autonomous and occupantpiloted mode. By a semi- or fully-autonomous mode, we mean a mode ofoperation wherein a vehicle can be piloted by a computing device as partof a vehicle information system having sensors and controllers. Thevehicle can be occupied or unoccupied, but in either case the vehiclecan be piloted without assistance of an occupant. For purposes of thisdisclosure, an autonomous mode is defined as one in which each ofvehicle propulsion (e.g., via a powertrain including an internalcombustion engine and/or electric motor), braking, and steering arecontrolled by one or more vehicle computers; in a semi-autonomous modethe vehicle computer(s) control(s) one or two of vehicle propulsion,braking, and steering.

Disclosed herein is a method, comprising: receiving an occupant positionmeasurement from at least one of an acoustic and a light sensor,determining an estimated occupant size based on occupant weight,estimating a vehicle seat position based on the occupant positionmeasurement and estimated occupant size, and, controlling a vehicleoccupant safety device based on the estimated occupant size andestimated vehicle seat position. the estimated occupant size can bedetermined based on two anthropomorphic models, a first anthropomorphicmodel corresponding to an adult male model and a second anthropomorphicmodel corresponding to an adult female model. Which anthropomorphicmodel the occupant position most likely matches can be determined basedon determining occupant weight, including adult male model, adult femalemodel, or no model. The estimated vehicle seat position can bedetermined based on the occupant position measurement and the determinedanthropomorphic model.

A vehicle seat position can be estimated including determining whetherthe occupant position measurement is consistent with the determinedanthropomorphic model and a seat located at a mid-track position. Theoccupant position measurement can be determined based on transmittinginfrared light or ultrasonic waves from a vehicle dashboard in adirection and with a field of view that intercepts the occupant, at thevehicle seat position. The vehicle occupant safety device can becontrolled including determining retractor force for a passiverestraint, wherein determining the retractor force for a passiverestraint can be based on which anthropomorphic model is matched.Retractor force for an active restraint can be determined when noanthropomorphic model is matched to be a default retractor force. Thevehicle seat position based on determining an estimated seat trackposition and an estimated seat back angle, wherein a seat mid-trackposition is indicated based on the estimated seat track position and theestimated seat back angle and the occupant position measurementincluding a predetermined tolerance and wherein the occupant positionmeasurement is made between a portion of a vehicle dashboard and pointsin a field of view that includes a chest portion of one or more adultanthropomorphic models and the one or more adult anthropomorphic modelsinclude a 5^(th) percentile female adult anthropomorphic model and a50^(th) percentile adult male anthropomorphic model. Controlling avehicle occupant safety device can be based on matching the occupantdistance measurement with a 5^(th) percentile female adultanthropomorphic model, a 50^(th) percentile adult male anthropomorphicmodel if the distance measurement indicates a seat mid-track position.

Further disclosed is a computer readable medium storing programinstructions for executing some or all of the above method steps.Further disclosed is a computer programmed for executing some or all ofthe above method steps, including a computer apparatus, programmed toreceive an occupant position measurement from at least one of anacoustic and a light sensor, determine an estimated occupant size basedon occupant weight, estimate a vehicle seat position based on theoccupant position measurement and estimated occupant size, and, controla vehicle occupant safety device based on the estimated occupant sizeand estimated vehicle seat position. the estimated occupant size can bedetermined based on two anthropomorphic models, a first anthropomorphicmodel corresponding to an adult male model and a second anthropomorphicmodel corresponding to an adult female model. Which anthropomorphicmodel the occupant position most likely matches can be determined basedon determining occupant weight, including adult male model, adult femalemodel, or no model.

The computer can be programmed to estimate the vehicle seat positionbased on the occupant position measurement and the determinedanthropomorphic model. A vehicle seat position can be estimatedincluding determining whether the occupant position measurement isconsistent with the determined anthropomorphic model and a seat locatedat a mid-track position. The occupant position measurement can bedetermined based on transmitting infrared light or ultrasonic waves froma vehicle dashboard in a direction and with a field of view thatintercepts the occupant, at the vehicle seat position. The vehicleoccupant safety device can be controlled including determining retractorforce for a passive restraint, wherein determining the retractor forcefor a passive restraint can be based on which anthropomorphic model ismatched. Retractor force for an active restraint can be determined whenno anthropomorphic model is matched to be a default retractor force.

The computing device can be programmed to determine a vehicle seatposition based on determining an estimated seat track position and anestimated seat back angle, wherein a seat mid-track position isindicated based on the estimated seat track position and the estimatedseat back angle and the occupant position measurement including apredetermined tolerance and wherein the occupant position measurement ismade between a portion of a vehicle dashboard and points in a field ofview that includes a chest portion of one or more adult anthropomorphicmodels and the one or more adult anthropomorphic models include a 5^(th)percentile female adult anthropomorphic model and a 50^(th) percentileadult male anthropomorphic model. Controlling a vehicle occupant safetydevice can be based on matching the occupant distance measurement with a5^(th) percentile female adult anthropomorphic model, a 50^(th)percentile adult male anthropomorphic model if the distance measurementindicates a seat mid-track position.

FIG. 1 is a diagram of a vehicle information system 100 that includes avehicle 110 operable in autonomous (“autonomous” by itself in thisdisclosure means “fully autonomous”) and occupant piloted (also referredto as non-autonomous) mode in accordance with disclosed implementations.Vehicle 110 also includes one or more computing devices 115 forperforming computations for piloting the vehicle 110 during autonomousoperation. Computing devices 115 can receive information regarding theoperation of the vehicle from sensors 116.

The computing device 115 includes a processor and a memory such as areknown. Further, the memory includes one or more forms ofcomputer-readable media, and stores instructions executable by theprocessor for performing various operations, including as disclosedherein. For example, the computing device 115 may include programming tooperate one or more of vehicle brakes, propulsion (e.g., control ofacceleration in the vehicle 110 by controlling one or more of aninternal combustion engine, electric motor, hybrid engine, etc.),steering, climate control, interior and/or exterior lights, etc., aswell as to determine whether and when the computing device 115, asopposed to a human operator, is to control such operations.

The computing device 115 may include or be communicatively coupled to,e.g., via a vehicle communications bus as described further below, morethan one computing devices, e.g., controllers or the like included inthe vehicle 110 for monitoring and/or controlling various vehiclecomponents, e.g., a powertrain controller 112, a brake controller 113, asteering controller 114, etc. The computing device 115 is generallyarranged for communications on a vehicle communication network such as abus in the vehicle 110 such as a controller area network (CAN) or thelike; the vehicle 110 network can include wired or wirelesscommunication mechanism such as are known, e.g., Ethernet or othercommunication protocols.

Via the vehicle network, the computing device 115 may transmit messagesto various devices in the vehicle and/or receive messages from thevarious devices, e.g., controllers, actuators, sensors, etc., includingsensors 116. Alternatively, or additionally, in cases where thecomputing device 115 actually comprises multiple devices, the vehiclecommunication network may be used for communications between devicesrepresented as the computing device 115 in this disclosure. Further, asmentioned below, various controllers or sensing elements may providedata to the computing device 115 via the vehicle communication network.

In addition, the computing device 115 may be configured forcommunicating through a vehicle-to-infrastructure (V-to-I) interface 111with a remote server computer 120, e.g., a cloud server, via a network130, which, as described below, may utilize various wired and/orwireless networking technologies, e.g., cellular, BLUETOOTH® and wiredand/or wireless packet networks. Computing device 115 may be configuredfor communicating with other vehicles 110 through V-to-I interface 111using vehicle-to-vehicle (V-to-V) networks formed on an ad hoc basisamong nearby vehicles 110 or formed through infrastructure-basednetworks. The computing device 115 also includes nonvolatile memory suchas is known. Computing device 115 can log information by storing theinformation in nonvolatile memory for later retrieval and transmittalvia the vehicle communication network and a vehicle to infrastructure(V-to-I) interface 111 to a server computer 120 or user mobile device160.

As already mentioned, generally included in instructions stored in thememory and executed by the processor of the computing device 115 isprogramming for operating one or more vehicle 110 components, e.g.,braking, steering, propulsion, etc., without intervention of a humanoperator. Using data received in the computing device 115, e.g., thesensor data from the sensors 116, the server computer 120, etc., thecomputing device 115 may make various determinations and/or controlvarious vehicle 110 components and/or operations without a driver tooperate the vehicle 110. For example, the computing device 115 mayinclude programming to regulate vehicle 110 operational behaviors suchas speed, acceleration, deceleration, steering, etc., as well astactical behaviors such as a distance between vehicles and/or amount oftime between vehicles, lane-change, minimum gap between vehicles,left-turn-across-path minimum, time-to-arrival at a particular locationand intersection (without signal) minimum time-to-arrival to cross theintersection.

Controllers, as that term is used herein, include computing devices thattypically are programmed to control a specific vehicle subsystem.Examples include a powertrain controller 112, a brake controller 113,and a steering controller 114. A controller may be an electronic controlunit (ECU) such as is known, possibly including additional programmingas described herein. The controllers may communicatively be connected toand receive instructions from the computing device 115 to actuate thesubsystem according to the instructions. For example, the brakecontroller 113 may receive instructions from the computing device 115 tooperate the brakes of the vehicle 110.

The one or more controllers 112, 113, 114 for the vehicle 110 mayinclude known electronic control units (ECUs) or the like including, asnon-limiting examples, one or more powertrain controllers 112, one ormore brake controllers 113 and one or more steering controllers 114.Each of the controllers 112, 113, 114 may include respective processorsand memories and one or more actuators. The controllers 112, 113, 114may be programmed and connected to a vehicle 110 communications bus,such as a controller area network (CAN) bus or local interconnectnetwork (LIN) bus, to receive instructions from the computer 115 andcontrol actuators based on the instructions.

Sensors 116 may include a variety of devices known to provide data viathe vehicle communications bus. For example, a radar fixed to a frontbumper (not shown) of the vehicle 110 may provide a distance from thevehicle 110 to a next vehicle in front of the vehicle 110, or a globalpositioning system (GPS) sensor disposed in the vehicle 110 may providegeographical coordinates of the vehicle 110. The distance(s) provided bythe radar and/or other sensors 116 and/or the geographical coordinatesprovided by the GPS sensor may be used by the computing device 115 tooperate the vehicle 110 autonomously or semi-autonomously.

The vehicle 110 is generally a land-based autonomous vehicle 110 havingthree or more wheels, e.g., a passenger car, light truck, etc. Thevehicle 110 includes one or more sensors 116, the V-to-I interface 111,the computing device 115 and one or more controllers 112, 113, 114.

The sensors 116 may be programmed to collect data related to the vehicle110 and the environment in which the vehicle 110 is operating. By way ofexample, and not limitation, sensors 116 may include, e.g., altimeters,cameras, LIDAR, radar, ultrasonic sensors, infrared sensors, pressuresensors, accelerometers, gyroscopes, temperature sensors, pressuresensors, hall sensors, optical sensors, voltage sensors, currentsensors, mechanical sensors such as switches, etc. The sensors 116 maybe used to sense the environment in which the vehicle 110 is operating,where examples of environmental data include data about weatherconditions, the grade of a road, the location of a road or locations ofneighboring vehicles 110. The sensors 116 may further be used to collectdata including dynamic vehicle 110 data related to operations of thevehicle 110 such as velocity, yaw rate, steering angle, engine speed,brake pressure, oil pressure, the power level applied to controllers112, 113, 114 in the vehicle 110, connectivity between components andelectrical and logical health of the vehicle 110.

FIG. 2 is a diagram of an infrared (IR) LIDAR 200 that determines adistance D to a surface 208. IR LIDAR 200 can determine range ordistance to objects by directing an IR light emitting diode (LED) 202(labeled L) emitting pulses of IR light in a field of projection 206that reflect from a surface 208 and are received by an IR photodiode 204(labeled P), having a field of view 210 that overlaps the field ofprojection 206 at the surface 208. The IR LIDAR 200 can determine thedistance D by determining the elapsed time for an IR pulse to travelfrom IR LED 202, reflect from surface 208, and travel back to IRphotodiode 204. Since light travels about 30 centimeters (cm)/nanosecond(ns), determining the elapsed pulse time to within one ns can determinea distance D with a resolution of +/−30 cm, for example. Higher pulsetime resolutions can be used to determine distances with higherresolution. For example, pulse time resolution of 10 picoseconds (ps)can yield distance resolution of +/−3 millimeters (mm).

IR LIDAR 200 emits pulses of IR light in a field of projection 206. Thefield of projection 206 is a representation of the spatial distributionof IR light energy emitted by IR LED 202. The spatial distribution of IRlight energy emitted by IR LED 202 is a function of the diode junctionthat forms the light-emitting portion of IR LED 202 and opticalcomponents included in IR LED 202. Optical components can includelenses, filters, etc. that shape the output of the light emittingportion of IR LED 202 into a field of projection 206, which can be agraphical representation of IR light emission above a predeterminedlevel. The field of projection 206 can be shaped by optics included inIR LED 202 to project a pulse of IR light onto a surface 208 at apredetermined distance with a predetermined size and shape. This permitsoptics included in IR photodiode 204 to determine a field of view 210for IR photodiode 204 that overlaps the field of projection 206 andthereby permits IR photodiode 204 to acquire light energy from the pulseof IR light emitted by IR LED 202 and thereby permits IR LIDAR 200 todetermine a distance D by determining elapsed pulse time.

IR LIDAR 200 can be designed and constructed to be mounted in aninstrument panel, e.g., in a dashboard, in an interior portion of avehicle 110, and can have pulse energy and pulse time resolutionappropriate to emit IR pulses in a field of projection 206 and detect IRpulses in a field of view 210 to determine distance D from the IR LIDAR200 to an occupant or anthropomorphic model of an occupant seated in thevehicle 110. An anthropomorphic model of an occupant is a physical model(e.g. “crash test dummy”) that is constructed so that the size andproportions of the anthropomorphic model are equal to statisticalaverages of populations of humans. For example, adult male and adultfemale populations can be measured and the results processedstatistically to yield average size and proportions for adult males andadult females divided into percentiles by size. A representative adultmale anthropomorphic model can be determined by selecting ananthropomorphic model representing the 50^(th) percentile in size and arepresentative adult female anthropomorphic model representing the5^(th) percentile in size, for example.

FIG. 3 is a diagram of an ultrasonic range detector 300 that includes anultrasound transceiver 302. Ultrasound transducer 302 can include acrystal-based transducer that can emit ultrasonic waves in air based oninput electrical voltages and currents, and that can create outputelectrical voltages and currents based on received ultrasonic waves.Ultrasound range detector 300 can include a single ultrasound transducer302 to both transmit and receive ultrasonic waves, or can have separatetransmit and receive transducers. The ultrasound transducer 302 can beconfigured to emit ultrasonic waves in a field of projection 304 (dashedlines) that can reflect from a surface 306. The ultrasound transducercan also create electrical signals from the reflected ultrasonic wavesimpinging upon the ultrasound transducer from the field of view 308 ofthe ultrasound transceiver 302. Ultrasonic waves refer to sound wavesbeyond the range of human hearing, namely about 20K Hz. Ultrasonic waveshave properties that vary with the frequency of the waves. For example,air attenuates ultrasound as a function of frequency, making lowfrequency ultrasound (<100 K Hz) preferable for range detectors designedto operate in air.

Ultrasound transducer 302 can determine a distance D to a surface 306 byemitting a pulse of ultrasonic waves in a field of projection 304. Theultrasound transducer 302 can be designed to emit ultrasonic waves in afield of projection 304 having a predetermined size and shape at apredetermined distance. The field of view 308 of the ultrasoundtransducer 302 can be designed to overlap the field of projection 304and thereby permit ultrasound transducer 302 to emit a pulse ofultrasonic waves, and create an electrical signal based on receiving thepulse of ultrasonic waves reflected by a surface 306 and determining theelapsed pulse time for the pulse to travel from the ultrasoundtransducer 302 to the surface 306 and back. Since sound travels at 343meters (m)/s in dry air at sea level at 20° C., the distance D can bedetermined by measuring the elapsed pulse time at the appropriateresolution as discussed above in relation to FIG. 2.

Ultrasound range detector 300 can be designed and constructed to bemounted in a dashboard of an interior portion of a vehicle 110 and haveultrasonic pulse energy and pulse time resolution appropriate to emitultrasonic pulses in a field of projection 304 and detect ultrasonicpulses in a field of view 308 to determine a distance D from theultrasound range detector 300 to an occupant or anthropomorphic model ofan occupant seated in vehicle 110. The anthropomorphic model can be andadult male anthropomorphic model or an adult female anthropomorphicmodel as discussed above in relation to FIG. 2.

FIG. 4 is a diagram of a vehicle interior 400, including a seat 402 and,seated in the seat 402, an anthropomorphic model 404. Mounted in adashboard portion of vehicle interior 400, a distance sensor 406 (markedS) can determine a distance D_(o) from the distance sensor 406 to apoint p_(m) on anthropomorphic model 404 or an occupant seated in seat402. The distance sensor 406 can be an IR LIDAR 200 as discussed inrelation to FIG. 2, or an ultrasonic range detector 300 as discussed inrelation to FIG. 3. The distance sensor 406 can be mounted in either a“driver” position or one or more “passenger” positions in the frontseating portion of vehicle interior 400, for example, to determine adistance D_(o) from the dashboard to an occupant or anthropomorphicmodel, where “driver” and “passenger” positions are defined with respectto traditional occupant behavior in a vehicle 110.

Distance sensor 406 can be operatively connected to computing device 115included in vehicle 110 that includes vehicle interior 400 to permitcomputing device 115 to request and receive information from distancesensor 406 including distance D_(o). Computing device can input distanceD_(o), and, combined with information regarding estimated seat trackposition and estimated seat angle, determine if the distance D_(o) fitsan adult male anthropomorphic model 404, an adult female anthropomorphicmodel 404, or no anthropomorphic model 404.

The size and proportions of anthropomorphic model 404 can be based onstatistics determined by measuring populations of adult human males andfemales. The measurements can be divided by sex and grouped inpercentiles based on size. The adult male anthropomorphic model can bebased on the average size and proportions of the 50^(th) percentileadult human male. The adult female anthropomorphic model can be based onthe average size and proportions of the 5^(th) percentile adult humanfemale, where the percentiles are ranked from smallest to largest size.Assuming that seat 402 is at a mid-track position, and the seat angle αis within a predetermined tolerance of a nominal angle, computing device115 can determine if a measured distance D_(o) is consistent with a50^(th) percentile adult male anthropomorphic model 404, a 5^(th)percentile adult female anthropomorphic model 404, or no anthropomorphicmodel 404.

Vehicle seats such as seat 402 can include a seat track that permit theseat 402 to be set at various positions along the track. A seat trackposition can be defined as the location of reference point p_(s), onseat 402, along a reference line 408 substantially parallel to the seattrack. Computing device 115 can estimate the seat track position D_(st)in FIG. 4 based on measured distance D_(o) and a parameter b by theequation:

$\begin{matrix}{D_{st} = \frac{D_{o} + b}{\cos \mspace{14mu} \alpha}} & (1)\end{matrix}$

where D_(st) is a seat track position measured with respect to areference point in vehicle interior 400 and reference point s. Referencepoint s or seat track position, can be the point on reference line 408intersected by model line 410. Model line 410 is a line constructed topass through point p_(m) at seat angle α. The model line 410 isconstructed parallel to estimated seat back line 412, with seat angle αbeing set equal to the estimated angle of seat back line 412. The pointp_(s) is estimated to be where the model line 410 intersects referenceline 408.

The parameter b can derived from a 50^(th) percentile adult maleanthropomorphic model 404 and a 5^(th) percentile adult femaleanthropomorphic model 404 and can be determined by selecting a valuemeasured from the anthropomorphic features of the adult male and adultfemale anthropomorphic models 404:

$\begin{matrix}{b = \left\{ \begin{matrix}b_{5{th}} \\b_{50{th}} \\b_{x}\end{matrix} \right.} & (2)\end{matrix}$

where b_(5th) refers to a distance derived from features of a 5^(th)percentile adult female anthropomorphic model 404, b_(50th) refers to adistance derived from features of a 50^(th) percentile adult maleanthropomorphic model 404 and b_(x) refers to a distance that can bedetermined experimentally by determining a distance D_(o). Computingdevice 115 can determine if a vehicle 110 seat is occupied using a seatweight sensor, which measures the weight of an occupant and can acquireinformation regarding whether the weight matches the weight of a 50^(th)percentile adult male anthropomorphic model 404, a 5^(th) percentileadult female anthropomorphic model 404, or neither.

Once computing device 115 acquires model information regarding whichanthropomorphic model 404 is matched based on a seat weight sensor,computing device 115 can determine if a measured distance D_(o) isconsistent with, i.e., indicates, an anthropomorphic model 404 bydetermining if the distance D_(o) is consistent with seat 402 atmid-track position Dmid_(st). Seat 402 mid-track position Dmid_(st) canbe measured against a reference point in vehicle interior 400 for astart point of sensing system calibration while the seat is at mid-trackposition by the equation:

$\begin{matrix}{{Dmid}_{st} = \frac{{Dmid}_{0} + b}{\cos \mspace{14mu} \alpha}} & (3)\end{matrix}$

where Dmid₀ is the measured distance between sensor 406 and a pointp_(m) on an anthropomorphic model 404 while the seat 402 is at amid-track position. The threshold for detection of seat at a mid-trackposition is described by the equation:

$\begin{matrix}{{f({thresh})} = \left\{ \begin{matrix}{1,{{{Dmid}_{st} - \frac{\delta_{st}}{2}} < D_{st} \leq {{Dmid}_{st} + \frac{\delta_{st}}{2}}}} \\{{0,{otherwise}}\mspace{265mu}}\end{matrix} \right.} & (4)\end{matrix}$

Where δ_(st) is a predetermined tolerance on seat track position D_(st)that includes measurement error δ₀ related to model line 410. When aseat track position D_(st) is estimated based on a determined distanceD_(o), and the estimated seat track position D_(st) meets thresholdconditions in equation (4) (ƒ(thresh)=1), computing device 115 cancombine distance D_(o) with information regarding seat 402 occupancyacquired via sensors 116 included in seat 402 and previously determinedinformation regarding anthropomorphic models 404 to determine if themeasured distance D_(o) is consistent with an adult male anthropomorphicmodel 404 or an adult female anthropomorphic model 404. If the estimatedseat track position D_(st) does not meets threshold conditions inequation (4), (ƒ(thresh)=0), distance measure D_(o) is determined to beconsistent with seat 402 not being located at a mid-track position.

When computing device 115 determines that seat 402 is occupied and D_(o)is consistent with an 50^(th) percentile adult male anthropomorphicmodel 404, a second level retractor force can be applied to passiverestraints associated with an occupant of seat 402, for example shoulderand lap safety belts. When computing device 115 determines that seat 402is occupied and D_(o) is consistent with, i.e., indicates, an 5^(th)percentile adult female anthropomorphic model 404, a first levelretractor force can be applied to passive restraints associated with anoccupant of seat 402. Retractor force is a force applied to a passiverestraint by an actuator controlled by computing device 115 toelectro-mechanically, hydraulically, or pneumatically apply a controlledamount of tension to belts that form lap belts and shoulder harnessesincluded in a passive restraint system and can range from about 2kilonewtons (kN) to about 4.5 kN. A first level of retractor force canbe a low load force and a second level of retractor force can be a highload force. Applying retractor force based on an estimated size andweight of an occupant by matching a distance measure D₀ to ananthropomorphic model 404 can optimize the safe and effective operationof a passive restraint system.

FIG. 5 is a diagram of a flowchart, described in relation to FIGS. 1-4,of a process 500 for applying retractor force to passive restraintsbased on a distance measure. Process 500 can be implemented by aprocessor of computing device 115, taking as input information fromsensors 116, and executing instructions and sending control signals viacontrollers 112, 113, 114, for example. Process 500 includes multiplesteps taken in the disclosed order. Process 500 also includesimplementations including fewer steps or can include the steps taken indifferent orders.

Process 500 begins at step 502, in which a computing device 115 in avehicle 110 can detect an occupant in a seat 402 in a vehicle 110. Thiscan be in response to computing device 115 detecting an ignition switch“ON” event, or any other event indicating that the vehicle 110 can beginmoving, for example. At step 504 computing device 115 can direct adistance sensor 406 to determine a distance measure D_(o) from adashboard portion of a vehicle interior 400 to an occupant. At step 506computing device 115 can acquire, i.e. indicates, which anthropomorphicmodel 404 is matched based on an occupant seat weight sensor, either a50^(th) percentile adult male anthropomorphic model 404, a 5^(th)percentile adult female anthropomorphic model 404, or no anthropomorphicmodel as discussed above in relation to FIG. 4.

At step 508 computing device 115 can determine a retractor force basedon the anthropomorphic model 404 determined at step 506 and the distancemeasure acquired at step 504. If an 5^(th) percentile adult femaleanthropomorphic model 404 is indicated, and (ƒ(thresh)=1), retractorforce can be set to a first level. If an 50^(th) percentile or aboveadult male anthropomorphic model 404 is determined at step 506,retractor force can be set to a second level. If no anthropomorphicmodel 404 is determined at step 506, or (ƒ(thresh)=0), retractor forcecan be set to a default value. At step 510 the retractor forcedetermined at step 508 can be applied to passive restraints, for exampleseat and shoulder belts as described above in relation to FIG. 4.Following this step process 500 ends.

FIG. 6 is a diagram of a flowchart, described in relation to FIGS. 1-4,of a process 600 for determining retractor force for passive restraintsin a process such as process 500, above. Process 600 can be implementedby a processor of computing device 115, taking as input information fromsensors 116, and executing instructions and sending control signals viacontrollers 112, 113, 114, for example. Process 600 includes multiplesteps taken in the disclosed order. Process 600 also includesimplementations including fewer steps or can include the steps taken indifferent orders.

Process 600 begins at step 602, in which computing device 115 in avehicle 110 can estimate a seat track position D_(st) based on adistance measure D_(o) and determine a threshold function ƒ(thresh)based on the estimated seat track position D_(st) as discussed above inrelation to FIG. 4. At step 604, computing device 115 checks to see ifƒ(thresh)=0. If ƒ(thresh)=0, then seat 402 is not at mid-track position.so process 600 branches to step 606, where retractor force can be set toa default value. At step 604, if ƒ(thresh)=1, distance measure D_(o) isconsistent with, i.e., indicates, an anthropomorphic model 404;therefore, process 600 branches to step 608. If computing device 115indicates a 5^(th) percentile adult female anthropomorphic model 404,process 600 branches to step 610 in which computing device 115 setsretractor force to a first level. At step 608, if computing device 115indicates a 50^(th) percentile or above, adult male anthropomorphicmodel 404, process 600 branches to step 612 where computing device 115sets retractor force to a second level. Following this step process 600ends.

Computing devices such as those discussed herein generally each includeinstructions executable by one or more computing devices such as thoseidentified above, and for carrying out blocks or steps of processesdescribed above. For example, process blocks discussed above may beembodied as computer-executable instructions.

Computer-executable instructions may be compiled or interpreted fromcomputer programs created using a variety of programming languagesand/or technologies, including, without limitation, and either alone orin combination, Java™, C, C++, Visual Basic, Java Script, Perl, HTML,etc. In general, a processor (e.g., a microprocessor) receivesinstructions, e.g., from a memory, a computer-readable medium, etc., andexecutes these instructions, thereby performing one or more processes,including one or more of the processes described herein. Suchinstructions and other data may be stored in files and transmitted usinga variety of computer-readable media. A file in a computing device isgenerally a collection of data stored on a computer readable medium,such as a storage medium, a random access memory, etc.

A computer-readable medium includes any medium that participates inproviding data (e.g., instructions), which may be read by a computer.Such a medium may take many forms, including, but not limited to,non-volatile media, volatile media, etc. Non-volatile media include, forexample, optical or magnetic disks and other persistent memory. Volatilemedia include dynamic random access memory (DRAM), which typicallyconstitutes a main memory. Common forms of computer-readable mediainclude, for example, a floppy disk, a flexible disk, hard disk,magnetic tape, any other magnetic medium, a CD-ROM, DVD, any otheroptical medium, punch cards, paper tape, any other physical medium withpatterns of holes, a RAM, a PROM, an EPROM, a FLASH-EEPROM, any othermemory chip or cartridge, or any other medium from which a computer canread.

All terms used in the claims are intended to be given their plain andordinary meanings as understood by those skilled in the art unless anexplicit indication to the contrary in made herein. In particular, useof the singular articles such as “a,” “the,” “said,” etc. should be readto recite one or more of the indicated elements unless a claim recitesan explicit limitation to the contrary.

The term “exemplary” is used herein in the sense of signifying anexample, e.g., a reference to an “exemplary widget” should be read assimply referring to an example of a widget.

The adverb “approximately” modifying a value or result means that ashape, structure, measurement, value, determination, calculation, etc.may deviate from an exact described geometry, distance, measurement,value, determination, calculation, etc., because of imperfections inmaterials, machining, manufacturing, sensor measurements, computations,processing time, communications time, etc.

In the drawings, the same reference numbers indicate the same elements.Further, some or all of these elements could be changed. With regard tothe media, processes, systems, methods, etc. described herein, it shouldbe understood that, although the steps of such processes, etc. have beendescribed as occurring according to a certain ordered sequence, suchprocesses could be practiced with the described steps performed in anorder other than the order described herein. It further should beunderstood that certain steps could be performed simultaneously, thatother steps could be added, or that certain steps described herein couldbe omitted. In other words, the descriptions of processes herein areprovided for the purpose of illustrating certain embodiments, and shouldin no way be construed so as to limit the claimed invention.

We claim:
 1. A method, comprising: receiving an occupant positionmeasurement from at least one of an acoustic and a light sensor;determining an estimated occupant size based on occupant weight;estimating a vehicle seat position based on the occupant positionmeasurement and estimated occupant size; and controlling a vehicleoccupant safety device based on the estimated occupant size andestimated vehicle seat position.
 2. The method of claim 1, furthercomprising: determining the estimated occupant size based on twoanthropomorphic models, a first anthropomorphic model corresponding toan adult male model and a second anthropomorphic model corresponding toan adult female model.
 3. The method of claim 2, further comprising:determining which anthropomorphic model the occupant position mostlikely matches based on determining occupant weight, including adultmale model, adult female model, or no model.
 4. The method of claim 3,further comprising: determining the estimated vehicle seat positionbased on the occupant position measurement and the determinedanthropomorphic model.
 5. The method of claim 4, further comprising:estimating a vehicle seat position including determining whether theoccupant position measurement is consistent with the determinedanthropomorphic model and a seat located at a mid-track position.
 6. Themethod of claim 1, further comprising: determining the occupant positionmeasurement based on transmitting infrared light or ultrasonic wavesfrom a vehicle dashboard in a direction and with a field of view thatintercepts the occupant, at the vehicle seat position.
 7. The method ofclaim 6 further comprising: controlling the vehicle occupant safetydevice includes determining retractor force for a passive restraint. 8.The method of claim 7, further comprising: determining the retractorforce for a passive restraint based on which anthropomorphic model ismatched.
 9. The method of claim 8, further comprising: determiningretractor force for an active restraint when no anthropomorphic model ismatched to be a default retractor force.
 10. The method of claim 5,further comprising: estimating the vehicle seat position based ondetermining an estimated seat track position and an estimated seat backangle.
 11. A computer apparatus, programmed to: receive an occupantposition measurement from at least one of an acoustic and a lightsensor; determine an estimated occupant size based on occupant weight;estimate a vehicle seat position based on the occupant positionmeasurement and estimated occupant size; and control a vehicle occupantsafety device based on the estimated occupant size and estimated vehicleseat position.
 12. The apparatus of claim 11, further comprising:determine the estimated occupant size based on two anthropomorphicmodels, a first anthropomorphic model corresponding to an adult malemodel and a second anthropomorphic model corresponding to an adultfemale model.
 13. The apparatus of claim 12, further comprising:determine which anthropomorphic model the occupant position most likelymatches based on determining occupant weight, including adult malemodel, adult female model, or no model.
 14. The apparatus of claim 13,further comprising: determine the estimated vehicle seat position basedon the occupant position measurement and the determined anthropomorphicmodel.
 15. The apparatus of claim 14, further comprising: estimate avehicle seat position including determine whether the occupant positionmeasurement is consistent with the determined anthropomorphic model anda seat located at a mid-track position.
 16. The apparatus of claim 1,further comprising: determining the occupant position measurement basedon transmitting infrared light or ultrasonic waves from a vehicledashboard in a direction and with a field of view that intercepts theoccupant, at the vehicle seat position.
 17. The apparatus of claim 16further comprising: control the vehicle occupant safety device includingdetermine retractor force for a passive restraint.
 18. The apparatus ofclaim 17, further comprising: determine the retractor force for apassive restraint based on which anthropomorphic model is matched. 19.The apparatus of claim 18, further comprising: determine retractor forcefor an active restraint when no anthropomorphic model is matched to be adefault retractor force.
 20. The apparatus of claim 15, furthercomprising: estimate the vehicle seat position based on determining anestimated seat track position and an estimated seat back angle.